Maximizing revenue in symmetric resource allocation systems when user utilities exhibit diminishing returns

Roie Zivan, Miroslav Dudík, Praveen Paruchuri, Katia Sycara

Research output: Contribution to conferencePaperpeer-review

Abstract

Consumers of resources in realistic applications (e.g., web, multimedia) typically derive diminishing-return utilities from the amount of resource they receive. A resource provider who is deriving an equal amount of revenue from each satisfied user (e.g., by online advertising), can maximize the number of users by identifying a satisfaction threshold for each user, i.e., the minimal amount of resource the user requires in order to use the service (rather than drop out). A straightforward approach is to ask users to submit their minimal demands (direct revelation). Unfortunately, self-interested users may try to manipulate the system by submitting untruthful requirements. We propose an incentive-compatible mechanism for maximizing revenue in a resource allocation system where users are ex-ante symmetric (same amount of revenue for any satisfied user) and have diminishing-return utility functions. Users are encouraged by the mechanism to submit their true requirements and the system aims to satisfy as many users as possible. Unlike previous solutions, our mechanism does not require monetary payments from users or downgrading of service. Our mechanism satisfies the number of users within a constant factor of the optimum. Our empirical evaluation demonstrates that in practice, our mechanism can be significantly closer to the optimum than implied by the worst-case analysis. Our mechanism can be generalized to settings when revenue from each user can differ. Also, under some assumptions and adjustments, our mechanism can be used to allocate resource periodically over time.

Original languageAmerican English
Pages1097-1098
Number of pages2
StatePublished - 1 Jan 2011
Externally publishedYes
Event10th International Conference on Autonomous Agents and Multiagent Systems 2011, AAMAS 2011 - Taipei, Taiwan, Province of China
Duration: 2 May 20116 May 2011

Conference

Conference10th International Conference on Autonomous Agents and Multiagent Systems 2011, AAMAS 2011
Country/TerritoryTaiwan, Province of China
CityTaipei
Period2/05/116/05/11

Keywords

  • Auction and mechanism design

All Science Journal Classification (ASJC) codes

  • Artificial Intelligence

Fingerprint

Dive into the research topics of 'Maximizing revenue in symmetric resource allocation systems when user utilities exhibit diminishing returns'. Together they form a unique fingerprint.

Cite this